Domino Data Lab

AUGUST 22, 2019

Many thanks to Addison-Wesley Professional for providing the permissions to excerpt “Natural Language Processing” from the book, Deep Learning Illustrated by Krohn , Beyleveld , and Bassens. The excerpt covers how to create word vectors and utilize them as an input into a deep learning model. Introduction.

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

O'Reilly on Data

JUNE 18, 2019

Machine learning solutions for data integration, cleaning, and data generation are beginning to emerge. “AI In this post, we shed some light on various efforts toward generating data for machine learning (ML) models. business and quality rules, policies, statistical signals in the data, etc.).

Machine Learning 259

Machine Learning Data Quality Statistics Modeling 259

datapine

AUGUST 14, 2019

To fully leverage the power of data science, scientists often need to obtain skills in databases, statistical programming tools, and data visualizations. It helps to automate and makes the usage of the R programming statistical language easier and much more effective. perfect for statistical computing and design.

Data Science 214

Data Science Statistics Business Intelligence Visualization 214

Cloudera

FEBRUARY 25, 2021

Cloudera has a front-row seat to organizational challenges as those enterprises make Machine Learning a core part of their strategies and businesses. The work of a machine learning model developer is highly complex. We work with the largest companies in the world to help tackle their most challenging ML problems.

Deep Learning 83

Deep Learning Machine Learning Forecasting Visualization 83

Smarten

APRIL 19, 2024

Vendors, service providers and analytics solution companies will package data products and design data management solutions to support business users in their interaction with suppliers, customers and stakeholders, and to inform and support customers and end users as they choose products and options.

Analytics 57

Analytics Predictive Modeling KPI Machine Learning 57

Domino Data Lab

JULY 28, 2021

Through a marriage of traditional statistics with fast-paced, code-first computer science doctrine and business acumen, data science teams can solve problems with more accuracy and precision than ever before, especially when combined with soft skills in creativity and communication. Math and Statistics Expertise.

Data Science 110

Data Science Statistics Recreation/Entertainment Predictive Analytics 110

Ontotext

DECEMBER 15, 2023

It includes only ML papers and related entities; this SPARQL query shows some statistics: papers tasks models datasets methods evaluations repos 376557 4267 24598 8322 2101 52519 153476 We can start with these repositories (most of them are on Github) and get all their topics. We can start with a connecting dataset like LinkedPapersWithCode.

Machine Learning 69

Machine Learning Interactive Deep Learning Statistics 69

IBM Big Data Hub

FEBRUARY 13, 2024

The compact design and touch-based interactivity seemed like a leap into the future. Generative AI represents a significant advancement in deep learning and AI development, with some suggesting it’s a move towards developing “ strong AI.” Remember how cool it felt when you first held a smartphone in your hand?

Enterprise 127

Enterprise Modeling Testing Data-driven 127

Occam's Razor

MARCH 30, 2017

Machine Learning | Marketing. Machine Learning | Analytics. People tend to use these phrases almost interchangeably: Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning. Deep Learning is a specific ML technique. Machine Learning | Marketing.

Marketing Analytics 166

Marketing Analytics Marketing Analytics Deep Learning 166

Smart Data Collective

MAY 8, 2022

From the statistics shown, this means that both AI and big data have the potential to affect how we work in the workplace. Above all, there needs to be a set methodology for data mining, collection, and structure within the organization before data is run through a deep learning algorithm or machine learning.

Big Data 106

Big Data Data Analytics Analytics Cost-Benefit 106

Domino Data Lab

AUGUST 10, 2021

At the center of every machine learning or artificial intelligence application is the ML/AI model that is built with data, algorithms and code. PyTorch: used for deep learning models, like natural language processing and computer vision. It’s used for developing deep learning models.

Modeling 64

Modeling IT Risk Management Deep Learning 64

O'Reilly on Data

JULY 28, 2020

It’s often difficult for businesses without a mature data or machine learning practice to define and agree on metrics. Products based on deep learning can be difficult (or even impossible) to develop; it’s a classic “high return versus high risk” situation, in which it is inherently difficult to calculate return on investment.

Marketing 362

Marketing Experimentation Metrics Testing 362

Domino Data Lab

JULY 28, 2021

Data science is a field at the convergence of statistics, computer science and business. In this article, take a deep dive into data science and how Domino’s Enterprise MLOps platform allows you to scale data science in your business. In fact, deep learning was first described theoretically in 1943.

Data Science 45

Data Science Machine Learning Statistics Deep Learning 45

IBM Big Data Hub

DECEMBER 20, 2023

Machine learning (ML) technologies can drive decision-making in virtually all industries, from healthcare to human resources to finance and in myriad use cases, like computer vision , large language models (LLMs), speech recognition, self-driving cars and more. What is machine learning?

Machine Learning 82

Machine Learning Modeling Deep Learning Predictive Modeling 82

datapine

NOVEMBER 19, 2019

AI refers to the autonomous intelligent behavior of software or machines that have a human-like ability to make decisions and to improve over time by learning from experience. Currently, popular approaches include statistical methods, computational intelligence, and traditional symbolic AI. Voice-as-User Interface (VUI).

Technology 279

Technology Internet of Things IT IoT 279

Sisense

APRIL 15, 2021

Augmented analytics (according to Gartner, which would know), uses technologies “such as machine learning [ML] and AI to assist with data preparation, insight generation, and insight explanation to augment how people explore and analyze data in analytics and BI platforms.” Tools of the AI trade.

Analytics 98

Analytics Data Science Modeling Machine Learning 98

DataRobot Blog

MAY 26, 2022

Validating Modern Machine Learning (ML) Methods Prior to Productionization. Validating Machine Learning Models. Last time , we discussed the steps that a modeler must pay attention to when building out ML models to be utilized within the financial institution.

Risk 52

Risk Modeling Metrics Business Objectives 52

Domino Data Lab

JULY 15, 2021

Originally created for software development, Python is used in a variety of contexts, including deep learning research and model deployment. RStudio is an IDE for the R language used primarily for statistical analysis as well as data visualization. Some common IDEs are RStudio and Jupyter Notebook.

Data Science 145

Data Science Visualization Modeling Enterprise 145

IBM Big Data Hub

APRIL 18, 2024

LLMs like ChatGPT are trained on massive amounts of text data, allowing them to recognize patterns and statistical relationships within language. While AGI promises machine autonomy far beyond gen AI, even the most advanced systems still require human expertise to function effectively. The AGI research field is constantly evolving.

Cost-Benefit 97

Cost-Benefit Modeling Manufacturing Interactive 97

Domino Data Lab

JUNE 23, 2019

Pete Skomoroch ’s “ Product Management for AI ”session at Rev provided a “crash course” on what product managers and leaders need to know about shipping machine learning (ML) projects and how to navigate key challenges. Be aware that machine learning often involves working on something that isn’t guaranteed to work.

Management 110

Management Machine Learning Experimentation Metrics 110

Domino Data Lab

MAY 8, 2019

I’ve been out themespotting and this month’s article features several emerging threads adjacent to the interpretability of machine learning models. Machine learning model interpretability. Other good related papers include: “ Towards A Rigorous Science of Interpretable Machine Learning ”. Not yet, if ever.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

FineReport

DECEMBER 19, 2019

When it comes to data analysis, from database operations, data cleaning, data visualization , to machine learning, batch processing, script writing, model optimization, and deep learning, all these functions can be implemented with Python, and different libraries are provided for you to choose. From Google.

Knowledge Discovery 98

Knowledge Discovery Visualization Experimentation Reporting 98

Domino Data Lab

JULY 22, 2019

why data governance, in the context of machine learning is no longer a “dry topic” and how the WSJ’s “global reckoning on data governance” is potentially connected to “premiums on leveraging data science teams for novel business cases”. He was saying this doesn’t belong just in statistics. Tukey did this paper.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Domino Data Lab

JULY 9, 2019

Wiggins advocated that data scientists find problems that impact the business; re-frame the problem as a machine learning (ML) task; execute on the ML task; and communicate the results back to the business in an impactful way. I still believe that data science is the craft of trying to apply machine learning to some real world problem.

Data Science 112

Data Science Machine Learning Advertising Modeling 112

IBM Big Data Hub

OCTOBER 12, 2023

Early iterations of the AI applications we interact with most today were built on traditional machine learning models. These models rely on learning algorithms that are developed and maintained by data scientists. This understanding can affect how the AI interacts with those around them.

Machine Learning 74

Machine Learning Deep Learning Interactive Modeling 74

Cloudera

NOVEMBER 3, 2021

Thanks to pioneers like Andrew NG and Fei-Fei Li, GPUs have made headlines for performing particularly well with deep learning techniques. Today, deep learning and GPUs are practically synonymous. While deep learning is an excellent use of the processing power of a graphics card, it is not the only use.

Deep Learning 116

Deep Learning Machine Learning Data Science Cost-Benefit 116

O'Reilly on Data

FEBRUARY 18, 2020

This year’s growth in Python usage was buoyed by its increasing popularity among data scientists and machine learning (ML) and artificial intelligence (AI) engineers. After several years of steady climbing—and after outstripping Java in 2017—Python-related interactions now comprise almost 10% of all usage.

Data-driven 335

Data-driven Software Statistics Marketing 335

Smart Data Collective

OCTOBER 14, 2019

Ludwig is a tool that allows people to build data-based deep learning models to make predictions. Ludwig is a TensorFlow-based toolbox that aims to allow people to use machine learning during their data work without having extensive prior knowledge. It allows secure and interactive SQL analytics at the petabyte scale.

Data Science 68

Data Science Machine Learning Big Data Interactive 68

O'Reilly on Data

MAY 21, 2019

Companies successfully adopt machine learning either by building on existing data products and services, or by modernizing existing models and algorithms. I will highlight the results of a recent survey on machine learning adoption, and along the way describe recent trends in data and machine learning (ML) within companies.

Machine Learning 238

Machine Learning Technology Deep Learning Data Science 238

O'Reilly on Data

MARCH 24, 2020

On the machine learning side, we are entering what Andrei Karpathy, director of AI at Tesla, dubs the Software 2.0 Before you even think about sophisticated modeling, state-of-the-art machine learning, and AI, you need to make sure your data is ready for analysis—this is the realm of data preparation.

Machine Learning 346

Machine Learning Statistics Data Quality Modeling 346

O'Reilly on Data

JANUARY 25, 2021

We’ve explored usage across all publishing partners and learning modes, from live training courses and online events to interactive functionality provided by Katacoda and Jupyter notebooks. AI, Machine Learning, and Data. Artificial intelligence, machine learning, and data.

Machine Learning 363

Machine Learning Software Testing Technology 363